Children’s failure to control variables may reflect adaptive decision-making
Bibliographic Data
| ID | 21641285 |
|---|---|
| Authors | Neil R Bramley (0000-0002-4141-8476, University of Edinburgh), Angela Jones (0000-0002-8955-3060, Max Planck Institute for Human Development), Todd M Gureckis (0000-0002-7139-4778, New York University), Azzurra Ruggeri (0000-0002-0839-1929, Max Planck Institute for Human Development, corresponding author) |
| Year | 2022 |
| Volume | 29 |
| Issue | 6 |
| Pages | 2314-2324 |
| Publication date | 2022-12-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Psychonomic Bulletin & Review (JOURNAL) |
| Journal identifiers | ISSN: 1069-9384 • E-ISSN: 1531-5320 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.3758/s13423-022-02120-1 |
| PMID | 35831679 |
| OpenAlex | W4285391815 |
| Language | EN |
| Citations received | 3 |
| References cited | 54 |
Changing one variable at a time while controlling others is a key aspect of scientific experimentation and a central component of STEM curricula. However, children reportedly struggle to learn and implement this strategy. Why do children’s intuitions about how best to intervene on a causal system conflict with scientific practices? Mathematical analyses have shown that controlling variables is not always the most efficient learning strategy, and that its effectiveness depends on the “causal sparsity” of the problem, i.e., how many variables are likely to impact the outcome. We tested the degree to which 7- to 13-year-old children ( n = 104) adapt their learning strategies based on expectations about causal sparsity. We report new evidence demonstrating that some previous work may have undersold children’s causal learning skills: Children can perform and interpret controlled experiments, are sensitive to causal sparsity, and use this information to tailor their testing strategies, demonstrating adaptive decision-making
Causal analysis · Causal model · Causal structure · Cognitive psychology · Curriculum · Child and Animal Learning Development · Computer Science · Educational Strategies and Epistemologies · Psychology · School Choice and Performance · Artificial Intelligence
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| Unique citing works | 3 |
|---|---|
| Citations per year | 1 |
| Citation span | 2023 - 2024 (2) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 3 |